Four Data Scientist Myths: Debunked

Posted May 10, 2016byCSS

Data science is all about mathematical and technology skills, right? Not necessarily. When it comes to hiring, managers who have tunnel vision can miss out on their truly ideal candidate. If you hold some common misconceptions about data science, it’s probably time to revamp your hiring strategy in order to connect with the right people to help you achieve success.

Data Scientist Myth #1 – It’s All About The Numbers

Successful data scientists must be able to collect, organize, analyze and synthesize data. But if they cannot communicate their findings and recommendations to non-technical leaders they will not be successful. Data scientists help guide business decisions, and the ability to communicate well with people who don’t “speak” data science is an absolute necessity. During the interview process, have data science candidates make a short presentation and be sure to include non-technical staff in that portion of the interview to accurately assess their ability to break down complex concepts.

Data Scientist Myth #2 – Data Scientists Are Developers

Many employers expect data scientists to be developers, and many candidates will arrive at your front door with some development experience. However, expecting your data scientists to be skilled in development and asking them to find the time to develop their own solutions once they are on the job is asking a bit much. Instead, look for the ability to work with developers strategically to handle the development of solutions. Thorough reference checks can lend insight into a data scientist’s ability to work well with members of the development staff.

Data Scientist Myth #3 – Data Doesn’t Change

Holding data science teams to the same model year in and year out is a recipe for failure. Technology advances at breakneck speed, making constant change an inevitability. As you conduct data science candidate searches, focus on uncovering agility, flexibility and a commitment to staying on top of changes and trends in the industry. Innovation is the key to any successful technology initiative, including business intelligence.

Data Scientist Myth #4 – You Only Need One Or Two Dedicated Data Scientists

Many businesses hire one or two dedicated data scientists that they mix into the IT team responsible for analytics and business intelligence. The bigger the company, the bigger that dedicated team must be in order to manage the vast amount of information being collected and ultimately, use it in meaningful ways. Creating a dedicated BI team that has unique responsibilities from the IT department can ensure data science initiatives are meaningful and generate real ROI.

If your organization is searching for data science talent who will add real business value, you need to have effective recruiting strategies in place. The IT experts at CSS can connect you with tech professionals who possess the skills you need to drive your business forward this year. Contact us today to get the conversation started.